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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Detect Recently Installed Software in Python
Uses subprocess to call pip and parse package metadata to list recently installed Python packages.
import subprocess
import sys
from datetime import datetime, timedelta
def detect_recently_installed(days=7):
"""Detect recently installed software packages."""
recent_packages = []
cutoff_date = datetime.now() - timedelta(days=days)
try:
# For pip-installed packages (Python packages)
…How to Download a List of URLs to a Directory in Python
This script downloads a list of URLs into a specified directory, creating the folder if needed and keeping original filenames.
import urllib.request
from pathlib import Path
def download_urls(url_list, directory):
"""Download each URL in url_list into directory, keeping original filenames."""
save_dir = Path(directory)
save_dir.mkdir(parents=True, exist_ok=True)
for url in url_list:
filename = url.rstrip('/').spl…How to Filter Docker Containers for Pruning in Python
Simulate Docker's container prune by filtering a JSON list for exited containers older than a cutoff, returning pruned IDs and space freed.
import json
from datetime import datetime, timedelta
def parse_docker_ps(json_output: str, older_than_hours: int = 24) -> list:
containers = json.loads(json_output)
cutoff = datetime.now() - timedelta(hours=older_than_hours)
return [
c for c in containers
if datetime.fromisoformat(c["crea…How to Find Stale GitHub Issues in Python
Filter a list of GitHub issues to find those not updated within a configurable number of days using Python datetime arithmetic.
import os
from datetime import datetime, timezone, timedelta
import re
# Simulated GitHub issue data structure
SAMPLE_ISSUES = [
{"number": 101, "title": "Login button not working", "updated_at": "2025-06-01T12:00:00Z", "assignee": "alice"},
{"number": 102, "title": "Fix database migration error", "updated_at…How to Generate an Inventory CSV of Installed pip Packages in Python
This script uses subprocess and csv to list all installed pip packages and write their names and versions into a CSV inventory file.
import subprocess
import csv
def get_installed_packages():
"""Return a list of (name, version) tuples for installed pip packages."""
result = subprocess.run(
["pip", "list", "--format=freeze"],
capture_output=True,
text=True,
check=True
)
packages = []
for line in r…How to Parse Terraform Plan Output in Python
Parse mock Terraform plan output text into structured add, change, and destroy lists using Python.
import json
from typing import Dict, List
def parse_terraform_plan_output(plan_output_text: str) -> Dict[str, List[str]]:
"""
Parses a mock Terraform plan output text into a structured dictionary.
"""
parsed: Dict[str, List[str]] = {"add": [], "change": [], "destroy": []}
for line in plan_output_…How to Perform a DNS Lookup for A Records in Python
Resolve a hostname to IPv4 A records using Python's built-in socket.getaddrinfo and return a sorted list of addresses.
import socket
def get_a_records(hostname):
"""Fetch A records (IPv4 addresses) for a given hostname."""
try:
# getaddrinfo with family AF_INET restricts to IPv4 (A records)
infos = socket.getaddrinfo(hostname, None, socket.AF_INET)
# Each info tuple: (family, type, proto, canonname, so…How to Scan Files Against a Malware Hash List in Python
Compare a file's SHA-256 hash against a known malware hash set and report whether it's clean or infected.
import hashlib
from pathlib import Path
# Mock file content (in real usage, read from disk)
MOCK_FILE_CONTENT = b"print('hello world')"
KNOWN_MALWARE_HASHES = {
"8d969eef6ecad3c29a3a629280e686cf0c3f5d5a86aff3ca12020c923adc6c92",
"5e884898da28047151d0e56f8dc6292773603d0d6aabbdd62a11ef721d1542d8",
}
def sha25…How to Scan Open Ports on a Host with Python
A Python function that uses socket.connect_ex to check for open TCP ports on a given host within a range and returns a list of open ports.
import socket
def scan_ports(host, start_port, end_port):
open_ports = []
for port in range(start_port, end_port + 1):
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.settimeout(0.5)
result = sock.connect_ex((host, port))
if result == 0:
open_ports.app…How to Validate SSL Certificates for Multiple Domains in Python
A Python utility that checks SSL certificate expiry dates for a list of domains using the standard library ssl and socket modules.
import ssl
import socket
from datetime import datetime
def check_ssl_certificate(hostname: str, port: int = 443) -> dict:
"""Validate SSL certificate for a given hostname."""
context = ssl.create_default_context()
with socket.create_connection((hostname, port), timeout=5) as sock:
with context.wra…How to Write an IP Block List to hosts.deny in Python
This Python script validates a list of IP addresses and CIDR ranges, then writes them to a hosts.deny file to block connections at the TCP wrapper level.
from ipaddress import ip_network
def write_hosts_deny(ip_list, output_file="hosts.deny"):
with open(output_file, "w") as f:
for ip in ip_list:
try:
ip_network(ip)
f.write(f"ALL: {ip}\n")
except ValueError:
continue
print(f"Written…Mock Certbot Renewal in Python for Testing
Simulates a Let's Encrypt certificate renewal by writing a mock certificate file and printing realistic certbot CLI output, without calling the actual certbot.
import subprocess
import sys
from datetime import datetime, timedelta
from pathlib import Path
def renew_cert(domain: str, output_dir: str = "certs") -> str:
"""Simulate a Let's Encrypt renewal with mock certbot output."""
out = Path(output_dir)
out.mkdir(parents=True, exist_ok=True)
cert_path = out…Attach Source File Metadata to Records in Python
Add a source filename field to each record in a list by merging a new key into every dictionary using a dict unpacking comprehension.
from pathlib import Path
import json
def attach_source_metadata(records, source_file):
"""Attach source filename metadata to each record."""
return [
{**record, "source": Path(source_file).name}
for record in records
]
if __name__ == "__main__":
source = "/data/raw/customers.csv"
…Filter Records by Required Fields in Python
Filter a list of dictionaries, keeping only records where every required field is present and not None.
def filter_records(records, required_fields):
"""Return only records that have all required fields non-null."""
return [
record for record in records
if all(record.get(field) is not None for field in required_fields)
]
if __name__ == "__main__":
sample_records = [
{"name": "Al…How to Count JSON Records in Python
Read a JSON file and count the number of top-level records, handling both list and dictionary structures.
import json
from pathlib import Path
def count_records(json_file):
"""Count top-level records in a JSON file."""
with open(json_file, "r") as f:
data = json.load(f)
# Handle both list of records and dict of records
if isinstance(data, list):
return len(data)
elif isinstance(da…How to Explode an Array Field into Multiple Rows in Python
This code flattens a list of dictionaries by exploding each array field value into its own row, duplicating the other fields as needed.
from collections import defaultdict
data = [
{"id": 1, "name": "Alice", "tags": ["python", "data", "ai"]},
{"id": 2, "name": "Bob", "tags": ["web", "devops"]},
{"id": 3, "name": "Carol", "tags": []},
]
def explode_array_field(records, array_field):
result = []
for record in records:
for v…How to Filter Data in Python
Filter a list of dictionaries by exact key-value matches or numerical ranges using concise list comprehensions.
from typing import List, Dict, Any
def filter_data(
data: List[Dict[str, Any]], key: str, value: Any
) -> List[Dict[str, Any]]:
"""Return records where data[key] equals value."""
return [record for record in data if record.get(key) == value]
def filter_by_range(
data: List[Dict[str, Any]], key: str…How to Group Data by Key in Python
Group a list of dictionaries by a specified key using a defaultdict and compute per-group averages.
from collections import defaultdict
def group_by_key(data, key):
grouped = defaultdict(list)
for item in data:
grouped[item[key]].append(item)
return dict(grouped)
if __name__ == "__main__":
records = [
{"name": "Alice", "dept": "Engineering", "score": 85},
{"name": "Bob", "de…How to Group Rows by Key into Nested Arrays in Python
This code groups rows in a list of dictionaries by a specified key and returns a dictionary with each key mapped to a list of values from another key.
from collections import defaultdict
def implode_rows(rows, key, value_key):
grouped = defaultdict(list)
for row in rows:
grouped[row[key]].append(row[value_key])
return dict(grouped)
if __name__ == "__main__":
data = [
{"category": "fruit", "item": "apple"},
{"category": "fr…How to List Failed Records in a Dead Letter Queue Mock in Python
A mock Dead Letter Queue stores failed processing records with error details and timestamps, lists them, and exports to JSON.
import json
from datetime import datetime, timedelta
import random
class DeadLetterQueue:
def __init__(self):
self.failed_records = []
def add_failed_record(self, record_id, payload, error_message):
self.failed_records.append({
"record_id": record_id,
"payload": paylo…How to Merge Multiple Data Sources in Python
A beginner-friendly helper that merges lists of dictionaries from multiple sources into one combined list using key filtering.
import json
def merge_pipeline_data(*data_sources, keys=()):
"""Merge multiple data sources (list of dicts) into a single list of merged dicts.
Args:
*data_sources: One or more lists of dictionaries.
keys: Tuple of keys to include from each source (empty means all keys).
Returns:
…How to Reduce Aggregate Counts from Mapped Chunks in Python
Combine a list of mapped chunk dictionaries into a single aggregated count dictionary using functools.reduce.
from functools import reduce
from collections import defaultdict
def aggregate_chunks(mapped_chunks):
"""Combine mapped chunk counts into a single aggregate dict."""
return reduce(
lambda acc, chunk: {
**acc,
**{k: acc.get(k, 0) + v for k, v in chunk.items()}
},
…How to Sort a List of Dictionaries by Key in Python
A reusable helper function that sorts a list of dictionaries by a specified key, with optional descending order support.
from typing import List
def sort_records(records: List[dict], key: str, descending: bool = False) -> List[dict]:
"""Sort a list of dictionaries by a specified key."""
return sorted(records, key=lambda record: record[key], reverse=descending)
def demonstrate_sorting() -> None:
users = [
{"name": …How to Validate Data in a Python Pipeline
A helper module to validate common record types — email, positive integer, and non-empty string list — before processing data in a pipeline.
from typing import Any, Iterable
def is_valid_email(email: str) -> bool:
"""Basic email check: one '@', no spaces, dot after '@'."""
if "@" not in email or " " in email:
return False
local, _, domain = email.partition("@")
return bool(local) and "." in domain
def is_positive_int(value: Any)…Browse by section
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